Antenna Season Report Notebook¶

Josh Dillon, Last Revised January 2022

This notebook examines an individual antenna's performance over a whole season. This notebook parses information from each nightly rtp_summarynotebook (as saved to .csvs) and builds a table describing antenna performance. It also reproduces per-antenna plots from each auto_metrics notebook pertinent to the specific antenna.

In [1]:
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
In [2]:
# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "004"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder
In [3]:
# Use environment variables to figure out path to the csvs and auto_metrics
antenna = str(int(os.environ["ANTENNA"]))
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')

antenna = "74"
csv_folder = "/home/obs/src/H6C_Notebooks/_rtp_summary_"
auto_metrics_folder = "/home/obs/src/H6C_Notebooks/auto_metrics_inspect"
In [4]:
display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))

Antenna 74 Report

In [5]:
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna
In [6]:
# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, 'rtp_summary_table*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')

Found 32 csvs in /home/obs/src/H6C_Notebooks/_rtp_summary_
Found 32 auto_metrics notebooks in /home/obs/src/H6C_Notebooks/auto_metrics_inspect
In [7]:
# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0

def jd_to_summary_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'

def jd_to_auto_metrics_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'

Load relevant info from summary CSVs¶

In [8]:
this_antenna = None
jds = []

# parse information about antennas and nodes
for csv in csvs:
    df = pd.read_csv(csv)
    for n in range(len(df)):
        # Add this day to the antenna
        row = df.loc[n]
        if isinstance(row['Ant'], str) and '<a href' in row['Ant']:
            antnum = int(row['Ant'].split('</a>')[0].split('>')[-1]) # it's a link, extract antnum
        else:
            antnum = int(row['Ant'])
        if antnum != int(antenna):
            continue
        
        if np.issubdtype(type(row['Node']), np.integer):
            row['Node'] = str(row['Node'])
        if type(row['Node']) == str and row['Node'].isnumeric():
            row['Node'] = 'N' + ('0' if len(row['Node']) == 1 else '') + row['Node']
            
        if this_antenna is None:
            this_antenna = Antenna(row['Ant'], row['Node'])
        jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
        jds.append(jd)
        this_antenna.add_day(jd, row)
        break
In [9]:
# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]

df = pd.DataFrame(to_show)

# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
    df[col] = bar_cols[col]

z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
    df[col] = z_score_cols[col]

ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
    df[col] = ant_metrics_cols[col]

redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]   
for col in redcal_cols:
    df[col] = redcal_cols[col]

# style dataframe
table = df.style.hide_index()\
          .applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
          .background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
          .background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
          .applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
          .format({col: '{:,.4f}'.format for col in z_score_cols}) \
          .format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
          .format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
          .set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])

Table 1: Per-Night RTP Summary Info For This Atenna¶

This table reproduces each night's row for this antenna from the RTP Summary notebooks. For more info on the columns, see those notebooks, linked in the JD column.

In [10]:
display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))

Antenna 74, Node N05:

Out[10]:
JDs A Priori Status Auto Metrics Flags Dead Fraction in Ant Metrics (Jee) Dead Fraction in Ant Metrics (Jnn) Crossed Fraction in Ant Metrics Flag Fraction Before Redcal Flagged By Redcal chi^2 Fraction ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score Average Dead Ant Metric (Jee) Average Dead Ant Metric (Jnn) Average Crossed Ant Metric Median chi^2 Per Antenna (Jee) Median chi^2 Per Antenna (Jnn)
2460015 RF_maintenance 0.00% 0.00% 0.00% 0.00% - - -0.771079 -0.066737 -0.333893 -0.385920 -0.412096 1.625145 -1.177194 1.869728 0.6149 0.6241 0.3497 nan nan
2460014 RF_maintenance 100.00% 0.00% 0.00% 0.00% - - -0.740797 0.425567 -0.466528 -0.392031 1.135618 2.543367 -0.703426 5.155593 0.5905 0.6010 0.3545 nan nan
2460013 RF_maintenance 0.00% 0.00% 0.00% 0.00% - - -0.745474 -0.077495 -0.245316 -0.462585 -0.507308 0.795612 -1.024802 3.089435 0.6099 0.6250 0.3571 nan nan
2460012 RF_maintenance 100.00% 0.00% 0.00% 0.00% - - -0.709533 -0.099725 -0.363875 -0.644829 -0.395466 1.553735 0.268321 4.990479 0.6096 0.6231 0.3508 nan nan
2460011 RF_maintenance 0.00% 0.00% 0.00% 0.00% - - -0.893261 0.000327 -0.232350 -1.061868 -0.667508 2.257342 -1.207976 2.460746 0.6160 0.6279 0.3529 nan nan
2460010 RF_maintenance 0.00% 0.00% 0.00% 0.00% - - -0.759641 0.212965 0.244970 -0.406206 -0.507923 1.029080 -1.325728 1.877848 0.6255 0.6410 0.3566 nan nan
2460009 RF_maintenance 0.00% 0.00% 0.00% 0.00% - - -0.635486 0.120769 -0.037703 -0.551673 -0.587319 1.947469 -1.699763 0.833682 0.6224 0.6358 0.3675 nan nan
2460008 RF_maintenance 0.00% 0.00% 0.00% 0.00% - - -0.876225 0.079943 -0.019112 -0.570351 -0.769493 2.183490 -0.688498 0.503253 0.6672 0.6848 0.3214 nan nan
2460007 RF_maintenance 0.00% 0.00% 0.00% 0.00% - - -0.487656 0.445009 -0.223207 -0.268683 -0.683698 1.026788 -1.443063 3.711735 0.6351 0.6470 0.3438 nan nan
2459999 RF_maintenance 0.00% 89.06% 85.63% 0.00% - - nan nan nan nan nan nan nan nan 0.1319 0.1616 0.0517 nan nan
2459998 RF_maintenance 100.00% 0.00% 0.00% 0.00% - - -0.879261 -0.252030 0.306471 -0.870850 -0.601645 1.298811 -0.561626 4.470152 0.6268 0.6391 0.3739 nan nan
2459997 RF_maintenance 100.00% 0.00% 0.00% 0.00% - - -0.654576 0.166427 0.101643 -0.235395 -0.553868 1.305885 -0.629878 4.412259 0.6420 0.6563 0.3775 nan nan
2459996 RF_maintenance 0.00% 0.00% 0.00% 0.00% - - -0.083364 0.285327 -0.123543 -0.335109 -0.537313 1.636108 -1.065580 0.611337 0.6466 0.6555 0.3917 nan nan
2459995 RF_maintenance 0.00% 0.00% 0.00% 0.00% - - -0.888607 0.129110 -0.109051 -0.627075 -0.400969 1.836452 -1.072476 1.276875 0.6430 0.6550 0.3746 nan nan
2459994 RF_maintenance 0.00% 0.00% 0.00% 0.00% - - -0.749562 -0.007685 0.428777 -0.865025 -0.572817 0.928103 -1.387774 1.461166 0.6366 0.6475 0.3742 nan nan
2459993 RF_maintenance 0.00% 0.00% 0.00% 0.00% - - -1.061593 0.414240 0.135672 -0.443775 0.044868 2.168280 -0.997641 1.900106 0.6322 0.6561 0.3827 nan nan
2459991 RF_maintenance 0.00% 0.00% 0.00% 0.00% - - -1.345299 0.013029 0.013713 -0.344819 -0.174036 1.446803 -1.024383 2.226698 0.6413 0.6442 0.3776 nan nan
2459990 RF_maintenance 0.00% 0.00% 0.00% 0.00% - - -0.980030 -0.053736 0.008115 -0.414566 0.125767 1.098833 -0.486294 3.381127 0.6445 0.6492 0.3766 nan nan
2459989 RF_maintenance 0.00% 0.00% 0.00% 0.00% - - -0.929429 -0.135067 0.225930 -0.136830 -0.019081 1.122034 -0.603430 2.631396 0.6401 0.6476 0.3798 nan nan
2459988 RF_maintenance 0.00% 0.00% 0.00% 0.00% - - -1.096476 -0.318882 0.005630 -0.625800 -0.033105 1.697741 -0.874767 3.028135 0.6340 0.6415 0.3730 nan nan
2459987 RF_maintenance 100.00% 0.00% 0.00% 0.00% - - -0.478053 0.119238 -0.034688 -0.399727 -0.206639 1.309626 0.219750 4.533075 0.6441 0.6518 0.3674 nan nan
2459986 RF_maintenance 0.00% 0.00% 0.00% 0.00% - - -0.675309 0.181181 -0.015865 -0.568146 -0.162129 1.618217 -0.426019 1.787351 0.6516 0.6648 0.3242 nan nan
2459985 RF_maintenance 0.00% 0.00% 0.00% 0.00% - - -0.571204 0.071660 -0.123291 -0.412632 -0.685193 1.325732 -1.124588 3.068185 0.6319 0.6380 0.3704 nan nan
2459984 RF_maintenance 0.00% 0.00% 0.00% 0.00% - - -0.265699 0.447142 -0.005243 -0.514688 -0.431358 1.891020 0.739570 2.237432 0.6536 0.6601 0.3519 nan nan
2459983 RF_maintenance 0.00% 0.00% 0.00% 0.00% - - -0.796750 0.060741 -0.067891 -0.525677 -0.172419 1.425663 -0.167067 2.407142 0.6624 0.6840 0.3128 nan nan
2459982 RF_maintenance 0.00% 0.00% 0.00% 0.00% - - -1.181640 -0.703788 -0.483359 -0.139204 0.310467 1.240890 -0.940039 0.221580 0.7144 0.7203 0.2801 nan nan
2459981 RF_maintenance 0.00% 0.00% 0.00% 0.00% - - -1.212941 -0.115192 0.036705 -0.665046 0.012510 1.031769 -0.838602 3.394905 0.6408 0.6489 0.3694 nan nan
2459980 RF_maintenance 0.00% 0.00% 0.00% 0.00% - - -0.982933 0.046763 -0.257635 -0.455464 -0.076487 0.260159 -0.914945 0.018572 0.6852 0.6966 0.3007 nan nan
2459979 RF_maintenance 0.00% 0.00% 0.00% 0.00% - - -1.346506 -0.050870 -0.157316 -0.496528 0.232185 1.157927 -0.608923 2.854996 0.6310 0.6426 0.3696 nan nan
2459978 RF_maintenance 100.00% 0.00% 0.00% 0.00% - - -1.341501 -0.005617 -0.023707 -0.621417 0.183805 1.616103 -0.034888 5.597204 0.6295 0.6404 0.3753 nan nan
2459977 RF_maintenance 100.00% 0.00% 0.00% 0.00% - - -0.992938 0.259956 -0.148609 -0.501270 0.951021 1.727730 -0.132002 4.341197 0.6015 0.6143 0.3419 nan nan
2459976 RF_maintenance 0.00% 0.00% 0.00% 0.00% - - -1.245846 0.045627 -0.152972 -0.589195 0.083309 1.168172 -0.633855 2.969696 0.6454 0.6539 0.3667 nan nan

Load antenna metric spectra and waterfalls from auto_metrics notebooks.¶

In [11]:
htmls_to_display = []
for am_html in auto_metric_htmls:
    html_to_display = ''
    # read html into a list of lines
    with open(am_html) as f:
        lines = f.readlines()
    
    # find section with this antenna's metric plots and add to html_to_display
    jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
    try:
        section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
    except ValueError:
        continue
    html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
    for line in lines[section_start_line + 1:]:
        html_to_display += line
        if '<hr' in line:
            htmls_to_display.append(html_to_display)
            break

Figure 1: Antenna autocorrelation metric spectra and waterfalls.¶

These figures are reproduced from auto_metrics notebooks. For more info on the specific plots and metrics, see those notebooks (linked at the JD). The most recent 100 days (at most) are shown.

In [12]:
for i, html_to_display in enumerate(htmls_to_display):
    if i == 100:
        break
    display(HTML(html_to_display))

Antenna 74: 2460015

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
74 N05 RF_maintenance nn Temporal Discontinuties 1.869728 -0.066737 -0.771079 -0.385920 -0.333893 1.625145 -0.412096 1.869728 -1.177194

Antenna 74: 2460014

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
74 N05 RF_maintenance nn Temporal Discontinuties 5.155593 -0.740797 0.425567 -0.466528 -0.392031 1.135618 2.543367 -0.703426 5.155593

Antenna 74: 2460013

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
74 N05 RF_maintenance nn Temporal Discontinuties 3.089435 -0.745474 -0.077495 -0.245316 -0.462585 -0.507308 0.795612 -1.024802 3.089435

Antenna 74: 2460012

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
74 N05 RF_maintenance nn Temporal Discontinuties 4.990479 -0.709533 -0.099725 -0.363875 -0.644829 -0.395466 1.553735 0.268321 4.990479

Antenna 74: 2460011

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
74 N05 RF_maintenance nn Temporal Discontinuties 2.460746 -0.893261 0.000327 -0.232350 -1.061868 -0.667508 2.257342 -1.207976 2.460746

Antenna 74: 2460010

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
74 N05 RF_maintenance nn Temporal Discontinuties 1.877848 -0.759641 0.212965 0.244970 -0.406206 -0.507923 1.029080 -1.325728 1.877848

Antenna 74: 2460009

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
74 N05 RF_maintenance nn Temporal Variability 1.947469 -0.635486 0.120769 -0.037703 -0.551673 -0.587319 1.947469 -1.699763 0.833682

Antenna 74: 2460008

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
74 N05 RF_maintenance nn Temporal Variability 2.183490 0.079943 -0.876225 -0.570351 -0.019112 2.183490 -0.769493 0.503253 -0.688498

Antenna 74: 2460007

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
74 N05 RF_maintenance nn Temporal Discontinuties 3.711735 -0.487656 0.445009 -0.223207 -0.268683 -0.683698 1.026788 -1.443063 3.711735

Antenna 74: 2459999

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
74 N05 RF_maintenance nn Shape nan nan nan nan nan nan nan nan nan

Antenna 74: 2459998

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
74 N05 RF_maintenance nn Temporal Discontinuties 4.470152 -0.879261 -0.252030 0.306471 -0.870850 -0.601645 1.298811 -0.561626 4.470152

Antenna 74: 2459997

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
74 N05 RF_maintenance nn Temporal Discontinuties 4.412259 -0.654576 0.166427 0.101643 -0.235395 -0.553868 1.305885 -0.629878 4.412259

Antenna 74: 2459996

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
74 N05 RF_maintenance nn Temporal Variability 1.636108 -0.083364 0.285327 -0.123543 -0.335109 -0.537313 1.636108 -1.065580 0.611337

Antenna 74: 2459995

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
74 N05 RF_maintenance nn Temporal Variability 1.836452 -0.888607 0.129110 -0.109051 -0.627075 -0.400969 1.836452 -1.072476 1.276875

Antenna 74: 2459994

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
74 N05 RF_maintenance nn Temporal Discontinuties 1.461166 -0.749562 -0.007685 0.428777 -0.865025 -0.572817 0.928103 -1.387774 1.461166

Antenna 74: 2459993

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
74 N05 RF_maintenance nn Temporal Variability 2.168280 -1.061593 0.414240 0.135672 -0.443775 0.044868 2.168280 -0.997641 1.900106

Antenna 74: 2459991

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
74 N05 RF_maintenance nn Temporal Discontinuties 2.226698 -1.345299 0.013029 0.013713 -0.344819 -0.174036 1.446803 -1.024383 2.226698

Antenna 74: 2459990

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
74 N05 RF_maintenance nn Temporal Discontinuties 3.381127 -0.053736 -0.980030 -0.414566 0.008115 1.098833 0.125767 3.381127 -0.486294

Antenna 74: 2459989

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
74 N05 RF_maintenance nn Temporal Discontinuties 2.631396 -0.135067 -0.929429 -0.136830 0.225930 1.122034 -0.019081 2.631396 -0.603430

Antenna 74: 2459988

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
74 N05 RF_maintenance nn Temporal Discontinuties 3.028135 -0.318882 -1.096476 -0.625800 0.005630 1.697741 -0.033105 3.028135 -0.874767

Antenna 74: 2459987

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
74 N05 RF_maintenance nn Temporal Discontinuties 4.533075 -0.478053 0.119238 -0.034688 -0.399727 -0.206639 1.309626 0.219750 4.533075

Antenna 74: 2459986

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
74 N05 RF_maintenance nn Temporal Discontinuties 1.787351 0.181181 -0.675309 -0.568146 -0.015865 1.618217 -0.162129 1.787351 -0.426019

Antenna 74: 2459985

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
74 N05 RF_maintenance nn Temporal Discontinuties 3.068185 0.071660 -0.571204 -0.412632 -0.123291 1.325732 -0.685193 3.068185 -1.124588

Antenna 74: 2459984

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
74 N05 RF_maintenance nn Temporal Discontinuties 2.237432 -0.265699 0.447142 -0.005243 -0.514688 -0.431358 1.891020 0.739570 2.237432

Antenna 74: 2459983

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
74 N05 RF_maintenance nn Temporal Discontinuties 2.407142 -0.796750 0.060741 -0.067891 -0.525677 -0.172419 1.425663 -0.167067 2.407142

Antenna 74: 2459982

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
74 N05 RF_maintenance nn Temporal Variability 1.240890 -1.181640 -0.703788 -0.483359 -0.139204 0.310467 1.240890 -0.940039 0.221580

Antenna 74: 2459981

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
74 N05 RF_maintenance nn Temporal Discontinuties 3.394905 -0.115192 -1.212941 -0.665046 0.036705 1.031769 0.012510 3.394905 -0.838602

Antenna 74: 2459980

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
74 N05 RF_maintenance nn Temporal Variability 0.260159 0.046763 -0.982933 -0.455464 -0.257635 0.260159 -0.076487 0.018572 -0.914945

Antenna 74: 2459979

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
74 N05 RF_maintenance nn Temporal Discontinuties 2.854996 -1.346506 -0.050870 -0.157316 -0.496528 0.232185 1.157927 -0.608923 2.854996

Antenna 74: 2459978

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
74 N05 RF_maintenance nn Temporal Discontinuties 5.597204 -0.005617 -1.341501 -0.621417 -0.023707 1.616103 0.183805 5.597204 -0.034888

Antenna 74: 2459977

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
74 N05 RF_maintenance nn Temporal Discontinuties 4.341197 -0.992938 0.259956 -0.148609 -0.501270 0.951021 1.727730 -0.132002 4.341197

Antenna 74: 2459976

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
74 N05 RF_maintenance nn Temporal Discontinuties 2.969696 0.045627 -1.245846 -0.589195 -0.152972 1.168172 0.083309 2.969696 -0.633855
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